Where change is welcome.
Data lakehouses are robust data platforms that unify the best features of data warehouses and lakes to produce a rich data solution. One such platform is Databricks. Built using open standards, it helps unify your storage, analytics, and Artificial Intelligence…
An overwhelming 97% of data engineers report burnout in their day-to-day jobs, citing repetitive tasks and fixing errors in the data lifecycle as the most common reason. For most organizations today, data arrives in droves from multiple locations. Manually loading…
Data is a valuable business asset, lying at the center of decision-making, customer satisfaction, and product development. However, data remains useless before it’s processed. The first step in processing involves extracting and transferring data from where they’re generated to storage…
While the Ingres database technology may have peaked in the 1980s, the tech is still in use, especially among large government and commercial organizations. But for a variety of reasons, it may be necessary to import an Ingres database to…
Newcomers to StreamSets might not know that we have three engines under the Control Hub hood: Data Collector, Transformer for Spark, and Transformer for Snowflake. This fact is easy to miss, because of how streamlined the experience is for users.…
Data federation tools are often touted for their ability to unify and query data in a variety of sources and formats using virtualization. The technology, the theory goes, provides a single, unified view of data without requiring you to manage…
Cloud data migration is on the rise, with cloud adoption expected to nearly double in the next five years. It's no surprise that cloud data migration is increasing, as many business benefits exist. In this piece, we’ll explore why organizations…
Standing for Extract, Transform, and Load, the acronym ETL describes the process of extracting data from a target, transforming it, and sending it on to load into a destination. The barest definition of ETL doesn’t include details about the nature…
Machine learning has become an integral part of organizations looking to do everything from improve customer experience to make product recommendations to target advertisements. The machine learning (ML) pipeline defines the steps that help create the models used for ML…
In the simplest terms, schema is the structure of data inside a database. The structure of data can include things like field and table names, views, indexes, and snapshots. The definition of schema will often expand to include the relationships…